Jörn, may you explain a bit more your proposal, please? We are not modifying the existing decimal datatype. This is how it works now. If you check the PR, the only difference is how we compute the result for the divsion operation. The discussion about precision and scale is about: shall we limit them more then we are doing now? Now we are supporting any scale <= precision and any precision in the range (1, 38].
Il giorno mer 9 gen 2019 alle ore 09:13 Jörn Franke <jornfra...@gmail.com> ha scritto: > Maybe it is better to introduce a new datatype that supports negative > scale, otherwise the migration and testing efforts for organizations > running Spark application becomes too large. Of course the current decimal > will be kept as it is. > > Am 07.01.2019 um 15:08 schrieb Marco Gaido <marcogaid...@gmail.com>: > > In general we can say that some datasources allow them, others fail. At > the moment, we are doing no casting before writing (so we can state so in > the doc). But since there is ongoing discussion for DSv2, we can maybe add > a flag/interface there for "negative scale intollerant" DS and try and cast > before writing to them. What do you think about this? > > Il giorno lun 7 gen 2019 alle ore 15:03 Wenchen Fan <cloud0...@gmail.com> > ha scritto: > >> AFAIK parquet spec says decimal scale can't be negative. If we want to >> officially support negative-scale decimal, we should clearly define the >> behavior when writing negative-scale decimals to parquet and other data >> sources. The most straightforward way is to fail for this case, but maybe >> we can do something better, like casting decimal(1, -20) to decimal(20, 0) >> before writing. >> >> On Mon, Jan 7, 2019 at 9:32 PM Marco Gaido <marcogaid...@gmail.com> >> wrote: >> >>> Hi Wenchen, >>> >>> thanks for your email. I agree adding doc for decimal type, but I am not >>> sure what you mean speaking of the behavior when writing: we are not >>> performing any automatic casting before writing; if we want to do that, we >>> need a design about it I think. >>> >>> I am not sure if it makes sense to set a min for it. That would break >>> backward compatibility (for very weird use case), so I wouldn't do that. >>> >>> Thanks, >>> Marco >>> >>> Il giorno lun 7 gen 2019 alle ore 05:53 Wenchen Fan <cloud0...@gmail.com> >>> ha scritto: >>> >>>> I think we need to do this for backward compatibility, and according to >>>> the discussion in the doc, SQL standard allows negative scale. >>>> >>>> To do this, I think the PR should also include a doc for the decimal >>>> type, like the definition of precision and scale(this one >>>> <https://stackoverflow.com/questions/35435691/bigdecimal-precision-and-scale> >>>> looks pretty good), and the result type of decimal operations, and the >>>> behavior when writing out decimals(e.g. we can cast decimal(1, -20) to >>>> decimal(20, 0) before writing). >>>> >>>> Another question is, shall we set a min scale? e.g. shall we allow >>>> decimal(1, -10000000)? >>>> >>>> On Thu, Oct 25, 2018 at 9:49 PM Marco Gaido <marcogaid...@gmail.com> >>>> wrote: >>>> >>>>> Hi all, >>>>> >>>>> a bit more than one month ago, I sent a proposal for handling properly >>>>> decimals with negative scales in our operations. This is a long standing >>>>> problem in our codebase as we derived our rules from Hive and SQLServer >>>>> where negative scales are forbidden, while in Spark they are not. >>>>> >>>>> The discussion has been stale for a while now. No more comments on the >>>>> design doc: >>>>> https://docs.google.com/document/d/17ScbMXJ83bO9lx8hB_jeJCSryhT9O_HDEcixDq0qmPk/edit#heading=h.x7062zmkubwm >>>>> . >>>>> >>>>> So I am writing this e-mail in order to check whether there are more >>>>> comments on it or we can go ahead with the PR. >>>>> >>>>> Thanks, >>>>> Marco >>>>> >>>>
